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Record W4311202436 · doi:10.2196/42575

Nigerian and Ghanaian Young People’s Experiences of Care for Common Mental Disorders in Inner London: Protocol for a Multimethod Investigation

2022· article· en· W4311202436 on OpenAlexvenueno aff
Anthony Isiwele, Carol Rivas, Gillian Stokes

Bibliographic record

VenueJMIR Research Protocols · 2022
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsnot available
FundersUniversity College LondonNational Institute for Health and Care Research
KeywordsProtocol (science)Mental healthPsychologyMedicineMedical educationGerontologyPsychiatryAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The Care Quality Commission published a review in 2018 in England titled "Are We Listening," which revealed that child and adolescent mental health services are not responsive to the specific needs of young Black people and other ethnic minorities even in areas with ethnically diverse populations. It found that commissioners and service planners failed to engage with these young people and their families to understand their needs and expectations. OBJECTIVE: The purpose of this study is to engage Nigerian and Ghanaian young people (NAGYP) with experiences of care for common mental disorders (CMDs) in London, to increase understanding of their needs, and to give voice to their views and preferences. Their parents', caregivers', and practitioners' views will also be sought for service improvement. METHODS: Three combined contemporary complementary methodologies-thematic analysis, interpretative phenomenological analysis (IPA), and intersectionality-based policy analysis (IBPA)-will be used across 3 comprehensive phases. First, a scoping review where relevant themes will be critically analyzed will inform further phases of this study. Detailed mapping of community and mental health care services in 13 inner London boroughs to investigate what professionals actually do rather than what they say they do. Second, IBPA will be used to scrutinize improving access to psychological therapies and other legislations and policies relevant to NAGYP to undertake an intersectional multileveled analysis of power, models, and constraints. Third, IPA will "give voice" and "make sense" of NAGYP lived experiences of CMDs via a representative sample of NAGYP participants' (n=30) aged 16-25 years, parents or caregivers' (n=20), and practitioners' (n=20) perspectives will be captured. RESULTS: The study has been approved by the UCL Institute of Education Research Ethics Committee (Z6364106/2022/02/28; health research) and University College London (Z6364106/2022/10/24; social research). Recruitment has begun in 13 inner boroughs of London. Data collection through observation, semistructured interviews, and focus groups are expected to be finalized by early 2024, and the study will be published by early 2025. CONCLUSIONS: Combining multiple qualitative methodologies and methods will enable rigorous investigation into NAGYP's lived experiences of care received for CMDs in London. Findings from this study should enable a reduction in the negative connotations and harmful superstitions associated with mental health-related issues in this group, inform evidence-based interventions, and facilitate preventive or early access to interventions. There may also be an indirect impact on problems resulting from mental illness such as school dropout, antisocial behaviors, knife crimes, juvenile detention centers, and even death. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/42575.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.102
metaresearch head score (Gemma)0.082
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.106
Threshold uncertainty score0.541

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1020.082
Meta-epidemiology (narrow)0.0040.005
Meta-epidemiology (broad)0.0070.007
Bibliometrics0.0080.008
Science and technology studies0.0090.006
Scholarly communication0.0070.007
Open science0.0050.006
Research integrity0.0080.009
Insufficient payload (model declined to judge)0.1060.016

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.192
GPT teacher head0.594
Teacher spread0.402 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2022
Admission routes1
Has abstractyes

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